Theoretical investigation of the effect of surface roughness on the fatigue life of austenitic stainless steels

Theoretical investigation of the effect of surface roughness on the fatigue life of austenitic stainless steels

Available online at ScienceDirect Materials Today: Proceedings 11 (2019) 417–422 ICMTMTE_2...

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ScienceDirect Materials Today: Proceedings 11 (2019) 417–422


Theoretical investigation of the effect of surface roughness on the fatigue life of austenitic stainless steels Hacı Bekir Özerkan* Gazi University Technical Sciences Vocational School, Ostim Mahallesi, Cevat Dündar Cad. No:19, Yenimahalle/Ankara, 06374 Turkey

Abstract After manufacturing, surface quality varies according to the type of manufacturing and cutting parameters. In this study, surface roughness measurements were performed after turning AISI 308 stainless steel in different machining parameters. Test samples prepared from steel in diameter 40 mm, length 200 mm were processed in CNC lathe machine in different cutting parameters. The highest roughness values were used for calculating the cross-sectional areas between the peak-valley points on surface profile. Using these roughness profile area values, theoretical fatigue life was calculated and evaluated due to the surface roughness. As a result, surface roughness tends to decrease with increasing cutting speed and theoretical fatigue life values have increased. The surface roughness has increased with the feed rate and fatigue life limit values have decreased. © 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Modern Trends in Manufacturing Technologies and Equipment 2018: Materials Science. Keywords: CNC turning; AISI 308 stainlees steel; surface roughnes; theoretical fatigue life

1. Introduction One of the most effective factor on the fatigue life of machine elements shaped by different manufacturing techniques is surface conditions. It is commonly known that fatigue cracks usually start from free surfaces. In strength science, the top surfaces of elements are directly exposed to external loads and are known to be the regions where stresses are most often caused by these loads [1]. After manufacturing, the surface roughness pattern is

* Corresponding author. Tel.: +90-505-289-0073; fax: +90-312-354-3835. E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Modern Trends in Manufacturing Technologies and Equipment 2018: Materials Science.


Hacı Bekir Özerkan / Materials Today: Proceedings 11 (2019) 417–422

different in all types of manufacturing. Furthermore, since different processing parameters are preferred for different materials in each manufacturing type, the surface integrity is also inevitable [2]. It is a fact that in machining, many machining parameters such as cutting speed, feed, tool geometry, work piece material, hardness and cooling liquid usage affect the surface integrity [3]. In a turning operation in which the 34CrNiMo6 steel bars gained a tensile strength of 1100 MPa by heat treatment, the effect of the feed rate and the surface integrity of the tool nose radius on the fatigue strength was investigated. As a result, it has been emphasized that the compressive residual stresses on the surfaces after machining are more effective on increasing the fatigue life than the surface roughness [4]. In another work in which the AISI 4130 steel is formed by turning, the roughness texture changes with the machining parameters and the surface roughness increment reduces the fatigue strength. It has also been found that the tensile stress factor (Kf) due to roughness on the treated surfaces varies between 1.01 and 1.08 [5]. In many studies in which bending fatigue tests have been carried out, it has been stated that the compressive residual stresses occurring after machining are increasing the fatigue life and also increment of roughness is the making reducing effect [6, 7]. Shortly, many researchers have stated that the amount of feed rate and chip depth values in the turning process is adversely affecting the surface roughness, and that the lowest roughness values can be obtained at an ideal cutting speed [8-10]. Therefore, in the turning process, different geometric surface texture is formed than in other manufacturing types. These various surface roughness geometries are also very influential on the fatigue life of the machine elements. The surface roughness of the peak and valley geometries is the stresses accumulate areas due to the external loads and the crack formation starts from these surfaces and fracture or breakage damage occurs with this mechanism. 2. Introduction 2.1. "√

" fatigue life estimation model

The most important parameters affecting the fatigue life of the metals in post-manufacturing evaluation are; surface roughness, surface hardness, residual stresses on the surface after machining, work hardening or softening due to plastic deformation, and change of microstructure on the surfaces [11]. It is difficult to analyze all of these effects as a whole. Therefore, it is more accurate to conduct the analysis operations separately and then evaluate them as a whole. In the fatigue model developed and accepted by Murakami, the surface roughness defined the wavy structure as a shallow interval and a deep notch, and defined the area of the peak and valley as √area (Fig. 1).

Fig. 1. Change in stress intensity factor for periodic surface roughness notches [11].

By modeling the surface roughness profile due to the fatigue life, the width and depth of the roughness wave are defined by expressions 2b and a, respectively. In this study, Rz(DIN) and Sm parameters expressing these definitions which are used in the theoretical fatigue calculations. Rz(DIN) is the average of the maximum peak and valley values (Rt) measured in the DIN measurement range and is schematically indicated in Fig.2. "Sm" is defined as the distance between the roughness peak points in the measurement length (Fig.2) and the term "2b" in the fatigue model. In fatigue calculations, these two measurement values which are standardized in roughness measurements are used.

Hacı Bekir Özerkan / Materials Today: Proceedings 11 (2019) 417–422

Rz( DIN) 


Rt1  Rt 2  Rt 3...............  Rtn n


Fig. 2. The maximum peak heights "Rt" and the distance between the peak points of roughness "Sm" according to the reference line.

In this study, the fully variable dynamic fatigue state is considered. Here, "√ " is the area size that expresses the profile waves on the surface. Equations 2 and 3 are equations for the range of roughness peak and pit values in the general fatigue life formula. (2) For a/2b < 0.195 ; (area)1/2/2b  2.97(a/2b)-3.51(a/2b)2-9.74(a/2b)3 For a/2b > 0.195 ; (area)1/2/2b  0.38 (3) 

1.43(Hv  120) 1  R  w  ( area)1/ 6  2 


In Equation 4, fatigue life estimation can be performed due to the surface roughness profile by substituting √ values. Where "w" is the allowable theoretical fatigue life and "α" is the stress sensitivity factor and is expressed as:

  0.226( HV *104 )


2.2. Material and experimental method In this work, the preparation of the test specimens was supplied from the AISI 308 steel, 40 mm in diameter with a circular cross section bar material, and its chemical composition and mechanical properties are given in Table 1. Table 1. Chemical composition of AISI 308 stainless steel Carbon, C 0.080 %

Chromium, Cr 20%

Iron, Fe 66%

Manganese, Mn 2.0 %

Nickel, Ni 11%

Phosphorous, P 0.045 %

Silicon, Si 1.0 %

Sulfur, S 0.030 %

In the study, three different cutting parameters were applied on cylindrical test samples. In order to measure the surface roughness, three pieces were obtained from a test sample. In turning, it is known from studies that the most influential variable is the feed rate in surface roughness according to other processing parameters. The cutting speed was changed with feed rate in processes, and the cutting depth was kept constant (Table 2). In the machining of the test specimens, tool insert and tool holder were used in the form of SNMG 12 04 08-MM 2220, which is supplied by the tool maker Sandvik. Cutting speeds of 150, 220 and 290 m/min are preferred from the optimum cutting speed range recommended by the manufacturer according to the preferred cutting insert. The effect of wear on the surface roughness at the cutting edge was prevented by using new tool for each machining in the experiments. Table 2. Cutting parameters of AISI 308 steel Exp. No V (m/min) f (mm/rev) a (mm)

1 150

2 220 0,2 2

3 290

4 150

5 220 0,4 2

6 290

7 150

8 220 0,6 2

9 290

10 150

11 220 0,8 2

12 290


Hacı Bekir Özerkan / Materials Today: Proceedings 11 (2019) 417–422

Surface roughness measurements were performed with the Mutitoyo Surftest SJ-210 portable device. In order to ensure the accuracy and reliability of the measurements, the measurements were taken from 4 different points and the average was used in the theoretical calculations. 3. Results and evaluation As a result, Ra, Rz(DIN) and Sm roughness parameters were measured. Increased cutting speed has been found to reduce the roughness values, but conversely the roughness increases with the feed rate increment. This change in surface quality is common in many studies [8-10]. The smallest Ra, Rz(DIN) and Sm values were obtained with V= 90m/min, f=0.2mm/r and a=2mm, values were 0.79m; 3.91m and 103.48m. And also the highest Ra, Rz (DIN) and Sm values were obtained for V=150m/min, f=0.8mm/r and a=2mm, values were 2.7m; 12.26m and 369.m respectively. Table 2. Cutting parameters, measurements and theoretical results. Deney No













V (m/min)


















a (mm)





Ra (m) Rz(DIN) (m) Sm (m) √area

























126,89 115,19 103,48 207,90 188,08 168,27 288,90 260,98 233,06 369,91 333,87 297,84 13,77












286,35 291,35 297,03 267,32 270,45 273,86 254,66 256,93 259,36 245,29 247,07 248,96














The roughness parameters Rz(DIN) and Sm on the surfaces produced by the machinings are chosen as the roughness measures which best represent the values a and 2b in the calculation of the √ expression. So, the theoretical fatigue limit stress and threshold stress intensity factor values were calculated using Rz (DIN) and Sm values in √ model and shown in Table 2. “√ ” is the average expression of the multiple measures of each peak-valley space area of the roughness profile in the fatigue equation. As the cutting speed increases, the surface roughness values decrease, so the √ values decrease (Fig. 3). However, with the increment of feed rate the roughness increased and the area values increased. The smallest area value was obtained as 11.05, V=290m/min at cutting speed and the feed rate value f=0.2mm/r. The maximum area value was found to be 34.84 at f=0.8mm/r at a cutting speed of V=150m/min. These values are a clear indication that the surface roughness decreases with the cutting speed and increases with the speed of the cutting in machining. Fatigue limit values determined by using these values increased with increase of area value and decreased with decrease (Fig. 3). The minimum limit fatigue life was determined as 245,29MPa at a cutting speed of V=150m/min, f=0,8mm/r and at the smallest roughness values (Rz(DIN)=12,26m; Sm=369,91m). And maximum limit fatigue life was determined as 297,03MPa at a cutting speed of V=290m/min, f=0,2mm/r and at the smallest roughness values (Rz(DIN)=3,91m; Sm=103,48m). This indicates that the increase in surface roughness is a discontinuity effect that reduces the fatigue life, so it has a notch effect. As the roughness increases, fatigue life is reduced. This indicates that the roughness is a significant effect of the field value of the top-valley regions, damage initiator and destructor. Here, stress intensity factor is a measure of the stress accumulation in surface roughness regions, depending on the surface roughness at the peak-valley points and wave structure of the roughness and its dimensions. Theoretical knowledge of the possible stress intensities on the surface of a fabricated machine element under the influence of operating forces can be used to estimate in which regions the damage will start.

Hacı Bekir Özerkan / Materials Today: Proceedings 11 (2019) 417–422


Kth (Threshold stress intensity factor)

Fatigue limit stress (MPa)


f=0,2mm/r f=0,4mm/r f=0,6mm/r f=0,8mm/r


290 280 270 260 250

3,0 2,8 2,6



V2=220m/min 2,2



240 140 160 180 200 220 240 260 280 300


Cutting speed (m/min)









Feed rate-f (mm/r)

f=0,2mm/r f=0,4mm/r f=0,6mm/r f=0,8mm/r

40 35


30 25 20 15 10 5 140 160 180 200 220 240 260 280 300

Cutting speed, V (m/min)

Fig. 3. Variation of σw (MPa), Kth and (area)1/2 due to the cutting speed (m/min) and feed rate (mm/r).

4. Conclusion AISI 308 steel specimens were machined by turning in the work and the theoretical fatigue life was determined depending on the surface roughness. At the same time, the threshold stress intensity factors were theoretically calculated using the " √ " fatigue model. The following results were obtained with the performed turning operations and theoretical calculations. The lowest surface roughness and the highest fatigue strength limit were observed when the cutting speed was 290m/min, progression was 0,2mm/d and chip depth was 2mm. In these processing conditions, the highest surface quality is achieved, the maximum fatigue life is determined. The worst surface quality was obtained when the cutting speed was 150 m/min and the feed rate was 0,8 mm/d. And the minimum fatigue life was specified in this machining. There is a directly proportional relationship between feed rate and surface roughness. The surface roughness is also increasing with the feed rate increment. In short, it has been found that the effect of feed rate surface roughness is more effective than the cutting speed. At low cutting speeds and at high feed rates, the highest


Hacı Bekir Özerkan / Materials Today: Proceedings 11 (2019) 417–422

surface roughness and depending on it the highest values of stress intensity factors were determined. This value means that the stress accumulation at the peak-valley areas in the roughness profile has reached high values. One of the most effective factor on the fatigue life of machine elements is surface roughness after turning operations. The pattern and size of the surface roughness produced is quite effective in the formation and development of fatigue damage. From the selected parameters, the feed rate increases the surface roughness more effectively. Thus, the maximum distance between the roughness peak points "Sm" and the average depth distance "Rz (DIN)" values between the peak-valley points increased. It is more appropriate that these two roughness expressions are preferred as a counterpart to the values of "a" and "2b" in the area model. References [1] Schmid, R. S., Hamrock, B. J., H., Jacobson, B.O., 2013. Fundamentals of Machine Elements (Third Edition), CRC Press, p. 161. [2] Davim, J.P. Surface integrity in machining, Vol. 1848828742. (Springer, 2010). [3] Ulutan, D. & Ozel, T. Machining induced surface integrity in titanium and nickel alloys: A review. International Journal of Machine Tools and Manufacture 51, 250-280 (2011). [4] Javidi, A., Rieger, U. & Eichlseder, W. The effect of machining on the surface integrity and fatigue life. International Journal of fatigue 30, 2050-2055 (2008). [5] Arola, D. & Williams, C. Estimating the fatigue stress concentration factor of machined surfaces. International Journal of fatigue 24, 923-930 (2002). [6] Davies, D. P., Jenkinsa, S. L., Legga, S. J., 2014. The Effect Machining Processes Can Have On the Fatigue Life and Surface Integrity of Critical Helicopter Components. Procedia CIRP 13, 25 – 30. [7] Torres, M., Voorwald, H., 2002. An Evaluation of Shot Peening, Residual Stress and Stress Relaxation on The Fatigue Life of AISI 4340 Steel. International Journal of Fatigue 24(8), 877-886. [8] Huang, L., Chen, C., 2001. A Multiple Regression Model to Predict In-process Surface Roughness in Turning. Journal of Industrial Technology, v.17 (2), 1-8. [9] Puertas, I., Luis Perez, C.J., 2003. Surface Rougness Prediction By Factorial Design of Experiments in Turning Processes. Journal of Materials Processing Technology, 143, 390-396. [10] Yamanea, Y., Ryutaroa, T., Tadanori, S., Ramirez I.M., Keiji, Y., 2017. A New Quantitative Evaluation For Characteristic of Surface Roughness in Turning, Precision Engineering, 50, 20–26 [11] Murakami, Y., 2002. Metal Fatigue: Effects of Small Defects and Nonmetallic Inclusions. Elsevier Science, Oxford, 305-320.